System and method to present a summarized task view in a case management system

ABSTRACT

A system and method is illustrated for providing information related to a task in a case management system configured to process a plurality of cases. The system and method includes identifying among the plurality of cases case clusters, for a case cluster of the case clusters, identifying task clusters, wherein each of task cluster is associated with a task similarity factor shared by at least two tasks of the task cluster, and tasks of the task clusters are performed on cases of the case cluster, analyzing reports and documents used to perform the at least two tasks of the task cluster sharing the task similarity factor, and when performing a task sharing the task similarity factor with the at least two tasks, providing at least one report based on the reports and at least one summary based on the documents.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of, and claims a benefit of priorityunder 35 U.S.C. 120 of the filing date of U.S. patent application Ser.No. 14/320,213, now U.S. Pat. No. 9,646,081, filed Jun. 30, 2014,“SYSTEM AND METHOD TO PRESENT A SUMMARIZED TASK VIEW IN A CASEMANAGEMENT SYSTEM”, the entire contents of which are hereby expresslyincorporated by reference for all purposes.

BACKGROUND

Skilled knowledge workers are valuable resources to any enterprise. Whenthese skilled workers are paid a fixed salary, an enterprise ismotivated to optimize worker productivity by ensuring that each workercan perform his tasks accurately and efficiently. By reducing the timethat each knowledge worker spends on each assigned task, more tasks canbe completed and the enterprise can be more efficient and costeffective.

Oftentimes, when a knowledge worker is assigned a task, he is generallyrequired to make a decision, such as, for example:

-   -   Should this insurance claim be approved?    -   Should this loan be approved with these particular terms?    -   Does this case require additional investigation?

To make such a decision, the knowledge worker typically must refer toinformation that is not necessarily specific to a case. For example, inorder to determine whether a loan should be approved in a certain regionor industry, the worker can refer to an analysis of demographicinformation in the region, or a report indicating trends in theparticular industry related to the loan. Utilizing such informationhelps the knowledge worker make better decisions that ultimately benefitthe enterprise and/or the customers.

The information required to make these decisions, however, is not alwaysobvious to the worker and, in many cases, is not explicitly included inthe task. As a result, the knowledge worker can spend considerable timeidentifying and searching for the needed information or may fail to findit altogether.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the system and method are described, by way ofexample, with respect to the following figures:

FIG. 1 is a block diagram illustrating an exemplary computingenvironment in which the subject matter may be implemented.

FIG. 2 is a diagram of an exemplary case management system illustratingtask performance by knowledge workers in the case management system.

FIG. 3 is a diagram of an exemplary case management system providinginformation related to a task according to an exemplary embodiment.

FIG. 4 is a diagram of an exemplary system illustrating the interactionbetween an activity monitor component and a list manager component toprovide a summarized task view.

FIG. 5 is an exemplary user interface illustrating a summarized taskview according to an exemplary embodiment.

FIG. 6 is a diagram of an exemplary case management system illustratinggenerating and using a summarized task view to perform a task in thecase management system according to an exemplary embodiment.

FIG. 7 is a diagram of an example computer implemented method executedto provide a summarized task view in a case management system accordingto an exemplary embodiment.

DETAILED DESCRIPTION

A detailed description of one or more example embodiments of a systemand method is provided below along with accompanying figures. While thissystem and method is described in conjunction with such embodiment(s),it should be understood that the system and method is not limited to anyone embodiment. On the contrary, the scope of the system and method islimited only by the claims and the system and method encompassesnumerous alternatives, modifications, and equivalents. For the purposeof example, numerous specific details are set forth in the followingdescription in order to provide a thorough understanding of the presentsystem and method. These details are provided for the purpose ofexample, and the system and method may be practiced according to theclaims without some or all of these specific details. For the purpose ofclarity, technical material that is known in the technical fieldsrelated to the system and method has not been described in detail sothat the present system and method is not unnecessarily obscured.

It should be appreciated that the present system and method may beimplemented in numerous ways, including as a process, an apparatus, adevice, or a computer-readable medium such as a computer-readablestorage medium containing computer-readable instructions or computerprogram code, or as a computer program product, comprising acomputer-usable medium having a computer-readable program code embodiedtherein. In the context of this disclosure, a computer-usable medium orcomputer-readable medium may be any medium that can contain or store theprogram for use by or in connection with the instruction executionsystem, apparatus or device. For example, the computer-readable storagemedium or computer-usable medium may be, but is not limited to, a randomaccess memory (RAM), read-only memory (ROM), or a persistent store, suchas a mass storage device, hard drives, CDROM, DVDROM, tape, erasableprogrammable read-only memory (EPROM or flash memory), or any magnetic,electromagnetic, infrared, optical, or electrical means or system,apparatus or device for storing information. Alternatively oradditionally, the computer-readable storage medium or computer-usablemedium may be any combination of these devices or even paper or anothersuitable medium upon which the program code is printed, as the programcode can be electronically captured, via, for instance, optical scanningof the paper or other medium, then compiled, interpreted, or otherwiseprocessed in a suitable manner, if necessary, and then stored in acomputer memory. Applications, software programs or computer-readableinstructions may be referred to as components or modules. Applicationsmay be hardwired or hard coded in hardware or take the form of softwareexecuting on a general purpose computer or be hardwired or hard coded inhardware such that when the software is loaded into and/or executed bythe computer, the computer becomes an apparatus for practicing thesystem and method. Applications may also be downloaded, in whole or inpart, through the use of a software development kit or toolkit thatenables the creation and implementation of the present system andmethod. In this specification, these implementations, or any other formthat the system and method may take, may be referred to as techniques.In general, the order of the steps of disclosed processes may be alteredwithin the scope of the system and method.

Techniques are described herein for presenting a summarized task view toknowledge workers in a case management system. The summarized task viewmay be automatically provided when tasks are assigned to the knowledgeworkers. The summarized task view may allow the knowledge workers tospend more time analyzing information pertinent to the task, and lesstime identifying and searching for, the information.

According to embodiments, a case management system is provided thatallows an enterprise to manage its business processes and/or salesoperations. For example, the case management system can manage aninsurance claim process or a loan application process for a case, i.e.,a specific insurance claim or a specific loan application, by breakingthe process into several tasks that are then assigned to knowledgeworkers who are trained and/or qualified to complete the tasks for thecase.

According to embodiments, when a knowledge worker is assigned on a task,the case management system can include a list manager component toprovide a summarized task view. The summarized task view may include alist of resources, such as reports and summaries of documents. Thereports and the summaries of documents may be generated based on theanalysis of an activity monitor component. The activity monitorcomponent may be configured to analyze reports and documents used toperform similar tasks.

In order to identify similar tasks, in embodiments, a case categorizercomponent may categorize a plurality of cases stored in the casemanagement system into a plurality of case clusters. A task categorizermay then identify task clusters for cases in each case cluster and, inan embodiment, categorize those tasks into task clusters. Once the casesare categorized by case clusters, and the tasks of the cases arecategorized by task clusters, the activity monitor may then monitor, inreal time, which resources (e.g., reports, documents, etc.) theknowledge worker searches for and accesses, and may determine why theknowledge worker uses those resources to complete the task. The activitymonitor component may monitor each knowledge worker's actions over aperiod of time and over a plurality of tasks, and may determine andstore the resources used to complete the tasks for the plurality ofcases.

According to embodiments, as the activity monitor component continuouslymonitors the system and generates analytic data, the list managercomponent can generate a resource list comprising reports, documents,and summaries of documents for each task cluster. The reports and thesummaries of documents of the task cluster with which the assigned taskis associated with may then be presented in the summarized task view tothe knowledge worker. In the summarized task view, the knowledge workermay view reports that are requested most by other knowledge workers whenperforming similar tasks and view document summaries generated by thesystem based on documents requests by other knowledge workers whenperforming similar tasks. Upon viewing the summaries, the knowledgeworker may also follow the links provided in the summarized task view toview full documents. Thus, when the summarized task view isautomatically provided along with the assigned task, the knowledgeworker can spend less time searching for relevant information tocomplete the task, thereby shortening the cycle time for the task andimproving overall process efficiency.

FIG. 1 is an example system 100, in which a case management environmentfor providing a summarized task view to knowledge workers assigned totasks may be implemented. The system 100 may include at least onecomputing device 110 operatively coupled to a data store 105 andcommunicatively coupled to at least one remote computing device 190 vianetwork 180. Exemplary computing devices 110 and 190 may includephysical or virtual desktop computers, servers, networking devices,notebook computers, PDAs, mobile phones, digital image capture devices,and the like. Through the computing devices 110 and 190, data may begenerated and stored on the data store 105. The data store 105 may thenprovide data to the knowledge workers when the knowledge workers senddata retrieval request to the computing device 110.

In embodiments, the data store 105 may include one or more storagedevices. These devices may be, for example, devices that store data onone or more types of media, including magnetic, optical, or other typeof media used for storing data. In this respect, it should beappreciated that data stored in the data store 105 may be stored on oneor more physical devices in the data store 105. As further shown in FIG.2 and FIG. 3, in embodiments, the data store 105 further includes aplurality data repositories for storing cases, work queues, andresources used in the case management system 100 for performing tasks incases.

In embodiments, the computing device 110 includes at least one processorunit 120, memory 130, storage 140, input device(s) 150, and outputdevice(s) 160. The processor 120 may be an instruction executionmachine, apparatus, or device and may comprise a microprocessor, adigital signal processor, a graphics processing unit, an applicationspecific integrated circuit (ASIC), a field programmable gate array(FPGA), etc. The processor unit 120 may be configured to execute programinstructions stored in the memory 130 and/or the storage 140.

The memory 130 may be volatile (such as RAM, for example), non-volatile(such as ROM, flash memory, etc., for example) or some combination ofthe two. The memory 130 may be configured to store program instructionsand data during operation of the computing device 110. In embodiments,the memory 130 may include any of a variety of memory technologies suchas static random access memory (SRAM) or dynamic RAM (DRAM), includingvariants such as dual data rate synchronous DRAM (DDR SDRAM), errorcorrecting code synchronous DRAM (ECC SDRAM), or RAMBUS DRAM (RDRAM),for example. The memory 130 may also include nonvolatile memorytechnologies such as nonvolatile flash RAM (NVRAM) or ROM. Inembodiments, the memory 130 may include a combination of technologiessuch as the foregoing, as well as other technologies not specificallymentioned.

In embodiments, the computing device 110 includes at least one storage140 (e.g., removable and/or non-removable). The storage 140 may includea flash memory data storage device for reading from and writing to flashmemory, a hard disk drive for reading from and writing to a hard disk, amagnetic disk drive for reading from or writing to a removable magneticdisk, and/or an optical disk drive for reading from or writing to aremovable optical disk such as a CD ROM, DVD or other optical media. Thedrives and their associated computer-readable media provide nonvolatilestorage of computer readable instructions, data structures, programmodules and other data for the computing device 110. In embodiments,computer readable instructions to implement embodiments provided hereinmay be stored in the storage 140. The storage 140 may also store othercomputer readable instructions to implement an operating system, anapplication program, program data, and the like. Computer readableinstructions may be loaded in the memory 130 for execution by theprocessor 120, for example.

The computing device 110 may include input device(s) 150, such as atleast one of a keyboard, mouse, pen, voice input device, touch inputdevice, scanner, satellite dish, still camera, video input device,and/or any other input device. Output device(s) 160, such as one or moredisplays, speakers, printers, and/or any other output device may also beincluded in the computing device 110. Input device(s) 150 and outputdevice(s) 160 may be operatively coupled to the computing device 110 viaa wired connection, wireless connection, or any combination thereof. Inembodiments, an input device or an output device from another computingdevice 190 may be operatively coupled to the computing device 110 andused as input device(s) 150 or output device(s) 160 for the computingdevice 110.

Components of the computing device 110 may be operatively coupled andconnected by various interconnects, such as a bus. Such interconnectsmay include a Peripheral Component Interconnect (PCI), such as PCIExpress, a USB, firewire, an optical bus structure, a local busstructure, and the like. In embodiments, components of the computingdevice 110 are interconnected by the network 180. For example, thememory 130 is comprised of multiple physical memory units located indifferent physical locations interconnected by the network 180.

Still referring to FIG. 1, the computing device 110 may also include atleast one communication interface 170 to communicate with at least oneremote computing device 190 via the network 180. The communicationinterface 170 may include, but not limited to, a modem, a NetworkInterface Card (NIC), an integrated network interface, a radio frequencytransmitter/receiver, an infrared port, a Universal Serial Bus (USB)connection, a network processing unit, or other interfaces forconnecting the computing device 110 to other computing devices 190. Theconnections to the network may include a wired connection or a wirelessconnection to transmit and/or receive data over communication media.

The remote computing device 190 may be another computer, a server, arouter, a peer device or other common network node, and may include thecomponents described above relative to the computing device 110. Thecommunication interface 170 may interface with a wireless and/or a wirednetwork 180. Examples of wireless networks include, for example, aBLUETOOTH network, a wireless personal area network, a wireless 802.11local area network (LAN), and/or wireless telephony network (e.g., acellular, PCS, or GSM network). Examples of wired networks include, forexample, a LAN, a fiber optic network, a wired personal area network, atelephony network, and/or a wide area network (WAN). Such networkingenvironments are commonplace in intranets, the Internet, offices,enterprise-wide computer networks and the like. In embodiments,communication interface 170 may include logic configured to supportdirect memory access (DMA) transfers between the memory 130 and otherdevices in the system 100.

The network 180 may provide connectivity among various components of thesystem 100 and may be implemented using the protocols such as TCP/IP, orsome other logical or physical connection. In embodiments, the network180 is implemented to provide support for various storage architecturessuch as Storage Area Network (SAN), Network-Attached Storage (NAS),Direct-Attached Storage (DAS), etc. Networks used to transfer databetween the computing devices 110 and 190 and the data store 105 mayinclude Fibre Channel, SCSI, Ethernet, Gigabit Ethernet, and other typesof communication networks. The support for various storage architecturesmay be used to provide the connection between the computing devices 110and 190 and the data store 105.

Those skilled in the art will realize that storage devices utilized tostore computer readable instructions may be distributed across thesystem 100. For example, a remote computing device 190 accessible viathe network 180 may store computer readable instructions to implementembodiments provided herein. The computing device 110 may access theremote computing device 190 and download the computer readableinstructions for execution. Alternatively, the computing device 110 maydownload the computer readable instructions, as needed, or someinstructions may be executed at the computing device 110 and some at theremote computing device 190.

It should be understood that the arrangement of system 100 illustratedin FIG. 1 is but one possible implementation and that other arrangementsare possible. It should also be understood that the various systemcomponents (and means) defined by the claims, described below, andillustrated in the various block diagrams represent logical componentsthat are configured to perform the functionality described herein. Forexample, one or more of these system components (and means) can berealized, in whole or in part, by at least some of the componentsillustrated in the arrangement of the computing device 110. In addition,while at least one of these components are implemented at leastpartially as an electronic hardware component, and therefore constitutesa machine, the other components may be implemented in software,hardware, or a combination of software and hardware. More particularly,at least one component defined by the claims is implemented at leastpartially as an electronic hardware component, such as an instructionexecution machine (e.g., a processor-based or processor-containingmachine) and/or as specialized circuits or circuitry (e.g., discretelogic gates interconnected to perform a specialized function), such asthose illustrated in FIG. 1. Other components may be implemented insoftware, hardware, or a combination of software and hardware. Moreover,some or all of these other components may be combined, some may beomitted altogether, and additional components can be added while stillachieving the functionality described herein. Thus, the subject matterdescribed herein can be embodied in many different variations, and allsuch variations are contemplated to be within the scope of what isclaimed.

In the description that follows, the subject matter will be describedwith reference to acts and symbolic representations of operations thatare performed by one or more devices, unless indicated otherwise. Assuch, it will be understood that such acts and operations, which are attimes referred to as being computer-executed, include the manipulationby the processing unit of data in a structured form. This manipulationtransforms the data or maintains it at locations in the memory system ofthe computer, which reconfigures or otherwise alters the operation ofthe device in a manner well understood by those skilled in the art. Thedata structures where data is maintained are physical locations of thememory that have particular properties defined by the format of thedata. However, while the subject matter is being described in theforegoing context, it is not meant to be limiting as those of skill inthe art will appreciate that variation of the acts and operationdescribed hereinafter may also be implemented in hardware.

To facilitate an understanding of the subject matter described below,many aspects are described in terms of sequences of actions. At leastone of these aspects defined by the claims is performed by an electronichardware component. For example, it will be recognized that the variousactions can be performed by specialized circuits or circuitry, byprogram instructions being executed by one or more processors, or by acombination of both. The description herein of any sequence of actionsis not intended to imply that the specific order described forperforming that sequence must be followed. All methods described hereincan be performed in any suitable order unless otherwise indicated hereinor otherwise clearly contradicted by context.

Referring now to FIG. 2, FIG. 2 is a diagram of an exemplary casemanagement system 200 illustrating task performance by knowledge workersin the case management system 200. The arrangement of components in FIG.2 may be implemented by components of the exemplary system 100 ofFIG. 1. The exemplary case management system 200 for a processing a casemay collect management data and/or case metadata for cases during a casemanagement process. Exemplary business processes include insurance claimprocesses, loan application processes, and the like.

The case management system 200 may include the data store 105, such as adatabase, configured to store information that may be used forprocessing cases. The data store 105 may include various datarepositories, such as a case repository 210 for storing cases and casemetadata, a work queue repository 230 for storing tasks in work queuesand task metadata, a configuration repository 220 for storingconfigurations of tasks, cases, and processes, and a resource repository240 for storing resources, among others. According to embodiments, theresources stored in the resource repository 240 may include documents,files, reports, forms, and links to websites and webpages that mayinclude helpful information.

When the case management system 200 is initially provided, configurationinformation of cases may be received, e.g., from a case managementadministrator, and stored in the configuration repository 220. Inembodiments, the configuration information may define a plurality ofphases in case management processes. For example, for an insurance claimcase process, phases can include a claim intake phase, an investigationphase, a liability determination phase, and a valuation phase. Inembodiments, each phase may be associated with a set of tasks that needto be completed by a knowledge worker in order for a case to progressthrough the case management process.

In addition, as shown in FIG. 2, the configuration information stored inthe configuration repository 220 may define case attributes that may bestandard attributes, e.g., along the timeline, a process/phase start andend date, or case specific attributes depending on a type of processbeing managed. For example, when the case management system 200 managesa bank loan application process, case attributes can correspond toinformation needed to process bank loan applications, e.g., job title,annual salary, existing debt, and the like. On the other hand, when thecase management system 200 manages an insurance claim process, caseattributes can correspond to claim type, accident type, date ofaccident, time of accident, and the like.

In addition to standard attributes, the configuration information storedin the configuration repository 220 may also include performancecriteria that define business goals and requirements, such as a servicelevel agreement (SLA) and/or in key performance indicators (KPIs). Likecase attributes and phases, performance criteria may be process specificdepending on the type of process being managed. For example, aperformance criterion for a bank loan application process can identify amaximum number of days in which a loan application must be completed.Similarly, a performance criterion for an insurance claim process canidentify a time limit of a phone call for collecting information about aclaimant.

In embodiments, the case management system 200 includes at least onework queue stored in the work queue repository 230. The work queue mayinclude a plurality of tasks, i.e. task 1, task 2 . . . task N,associated with a plurality of cases stored in the case repository 210.The tasks in the work queue repository 230 may be assigned to aplurality of knowledge workers. The knowledge workers may bespecifically trained to manage one or more types of tasks. For example,a work queue is associated with a contract review phase of a process andtasks in that work queue require knowledge of contract law. Such tasksmay be assigned to knowledge workers with legal training and/or in theenterprise's legal department.

According to embodiments, a task manager component 235 in the casemanagement system 200 is configured to manage task assignments. Forexample, when a task that needs to be completed is received and/oridentified, the task manager component 235 is configured to identifywhich skill is needed to complete the task and to add the task to thework queue corresponding to the skill. In addition, when a request for atask is received from a knowledge worker, the task manager component 235can be configured to determine the requesting knowledge worker's skillset based on, for example, the worker's role and/or department, toidentify at least one work queue in the work queue repository 230 thatmatches the skill set, and to assign a task from the matching work queueto the requesting knowledge worker. In this manner, the task manager 235may assign a plurality of tasks associated with a plurality of casesstored in the case repository 210 to the plurality of knowledge workers.In embodiment, the task manager component 235 maintains a task log thattracks which knowledge worker was assigned to perform which task. Thetask log may be operatively coupled to the task manager 235 and storedas part of the task manager component 235. Alternatively, the task logmay be stored in the data store 105 and operatively coupled to the workqueue repository 230.

In embodiments, a knowledge worker can receive an assigned taskassociated with a case from the task manager component 235. In manycases, the task may require the knowledge worker to make a decisionbased on case specific and/or non-case specific information. In theprocess of completing the task, the knowledge worker may use resourcesstored in the resource repository 240 to make a decision of the task. Inembodiments, the knowledge worker can identify a resource, e.g. adocument or a report, managed by the case management system 200 and cansend a request for the resource to a computing device in the casemanagement system 200. The case management system 200 may be configuredto receive the request and route the request to the task managercomponent 235. The task manager component 235 may invoke a data managercomponent 245 to retrieve the requested resource from the resourcerepository 240 and to transmit the resource to the requesting knowledgeworker.

To help the knowledge worker identifying the resource used in the task,the case management system 200 may provide a summarized task view. Anexemplary summarized task view user interface is illustrated in FIG. 4.Through the summarized task view, the knowledge worker may identify keyresources, such as reports generated most by other knowledge workerswhen performing similar tasks. And through the summarized task view, theknowledge worker may have quick access to summaries of key resources,such as summaries of documents generated by the system 200 fromdocuments used most by other knowledge workers when performing similartasks. When the summarized task view is automatically provided alongwith the assigned task, the knowledge worker may spend less timesearching for relevant information to complete the task, therebyshortening the cycle time for the task and improving overall processefficiency. FIG. 3 illustrates an exemplary system for generating thesummarized task view based on reports and documents used to performsimilar tasks.

FIG. 3 is a diagram of an exemplary case management system 300 forproviding information related to a task. In order to generate thesummarized task view, a computing device 110 may be used as a server toreceive resource requests from a remote computing device 190 via network180, manage and retrieve the data stored in the data store 105, andprovide the data to the remote computing device 190 via the network 180.

The server 110 may include a case categorizer 320, a task categorizer330 operatively coupled to the case categorizer 320, an activity monitor340 operatively coupled to the case categorizer 320 and the taskcategorizer 330, and a list manager 350 operatively coupled to theactivity monitor 340. Though FIG. 3 shown the server 110 as a separatecomponent, the server 110 may be configured as a plurality of componentsand/or be included in other components, such as the task manager 235and/or the data manager 245. Further, the server 110 may be configuredas a plurality of components to interact with more than one casemanagement system 300 in a distributed environment.

The case categorizer 320 may be configured to categorize the pluralityof cases stored in the case repository 210 into a plurality of caseclusters 324. Though not shown in FIG. 3, in embodiments, each casestored in the case repository 210 can include case metadata directed togeographical case specific parameters, such as a location or regionwhere the case originated and/or a preferred language forcommunications. The case metadata may also be directed to contextualcase specific parameters, such as a monetary value of the case, acustomer, a product ordered, etc.

According to embodiments, the case categorizer 320 can be configured tocollect the case metadata corresponding to the first plurality of casesstored in the case repository 210 and other case-related information,such as semantic entities extracted from case documents stored in thecase repository 210 and/or the resource repository 240, and to create atleast one data vector 322 for each of the first plurality of cases. Thecase categorizer 320 may then analyze the data vectors 322 to categorizethe cases into the plurality of case clusters 324. Alternatively or inaddition, the case categorizer 320 may be configured, in embodiments, tocollect the case metadata corresponding to the plurality of cases storedin the case repository 210 and the other case-related information, andto apply a clustering algorithm to identify the plurality of caseclusters 324. Though FIG. 3 shown the case cluster 324 being stored onthe server 110, the case cluster 324 may be stored outside the server110 in a separate repository or in other data storage, such as the datastore 105.

According to embodiments, each case cluster 324 is associated with acase similarity factor shared by at least two cases of the plurality ofcases, and each case of the plurality of cases is associated with a casecluster 324. The case categorizer 320 can be configured, in embodiments,to execute more than one clustering algorithm to generate different setsof case clusters 324 and then to compare and/or consolidate the sets todetermine an optimal set of case clusters 324. Such a determination maybe based on a minimum or maximum cluster size, the semantic value of thesimilarity factor associated with a cluster 324, and/or any otherclustering parameter.

In embodiments, the case similarity factor of a case cluster 324 isshared by cases in the case cluster 324. Because the cases in the casecluster 324 are clustered based on the case metadata, the casesimilarity factors are naturally related to at least one of geographicalcase specific parameters, a preferred communication language, andcontextual case specific parameters.

After each of the plurality of cases stored in the case repository 210has been associated with a case cluster 324, a plurality of taskclusters 332 may be identified for each of the plurality of caseclusters 324. Tasks of the plurality of task clusters 332 may beperformed on cases of the case cluster 324. Each task cluster 332 may beassociated with a similarity factor shared by at least two tasks of theplurality of tasks stored in the work queue repository 230, and eachtask of the first plurality of tasks may be associated with a taskcluster 332. According to embodiments, the server 110 can be configuredto identify the plurality of task clusters 332 for each of the pluralityof case clusters 324, where each task cluster is associated with asimilarity factor shared by at least two tasks of the plurality of tasksstored in the work queue 230.

In embodiments, the categorization of tasks into the task clusters 332may be performed by the task categorizer 330 in the server 110. Thetasks stored in the work queue 230 may be categorized into task clusters332 based on at least one similarity factor, which can be derived from asemantic analysis of information related to and/or relevant to eachtask. For example, the related and/or relevant information can includetask metadata related to a task and/or case metadata associated with anunderlying case for which the task is performed.

The task metadata related to the task can, in embodiments, be directedto task specific parameters that identify to which type of activity orfunction the task is directed, such as an investigation, a decision, areview or approval and/or a customer communication. The task metadatacan also be directed to a type of expertise needed to perform the task,such as high level math skills, communication skills, and/or computerprogramming skills. As stated above, the case metadata associated withthe first case can, in embodiments, be directed to geographical casespecific parameters, such as a location or region where the caseoriginated and/or a preferred language for communications. The casemetadata may also be directed to contextual case specific parameters,such as a monetary value of the case, a customer, a product ordered,etc.

According to embodiments, the task categorizer 330 can be configured tocollect the information related to and/or relevant to the plurality oftasks, e.g., the task metadata and case management data corresponding toeach task, and to apply a clustering algorithm to the informationrelated to and/or relevant to the plurality of tasks to identify thetasks clusters 332. In embodiments, the clustering algorithm can beselected from known clustering techniques such as, for example, K-meansclustering, fuzzy clustering, and QT clustering. The task categorizer330 may be configured, in embodiments, to execute more than oneclustering algorithm to generate different sets of task clusters 332 andthen to compare and/or consolidate the sets to determine an optimal setof task clusters 332. Such a determination may be based on a minimum ormaximum cluster size, the semantic value of the similarity factorassociated with a task cluster 332, and/or any other clusteringparameter.

In embodiments, the task similarity factor of a task cluster 332 isshared by tasks in the task cluster 332. Because the tasks are clusteredbased on the task metadata and case metadata, the task similarityfactors are naturally directed to at least task specific and casespecific parameters, and/or preferred communication languages, and taskexpertise. Accordingly, in embodiments, the task similarity factor maybe related to at least one of geographical case specific parameters, apreferred communication language, contextual case specific parameters,task specific parameters, and a type of expertise associated with thetask.

In embodiments, each task of the plurality of tasks stored in the workqueue 230 is included in a task cluster 332. For example, a task clusterassociated with a task similarity factor identifying loans originatingin a particular city, e.g., San Francisco, includes tasks that areassociated with a loan originating in San Francisco, and does notinclude a loan originating in Los Angeles. In another example, anothertask cluster is associated with a task similarity factor identifyingloans exceeding a threshold value, and each task in the cluster isassociated with a loan exceeding the threshold value. In embodiments,the task similarity factor of a task cluster 332 can be multifaceted inthat it can encompass more than one clustering condition. For example, atask cluster can be associated with a multifaceted similarity factoridentifying loans originating in San Francisco and exceeding thethreshold value. In embodiments, the task categorizer 330 can beconfigured to adjust and modify the task similarity factors of the taskclusters 332 such that each task of the plurality of tasks stored in thework queue 230 is included in one task cluster 332.

According to embodiments, the activity monitor component 340 can beconfigured to watch the case management system 300 and to monitor theactivities of the knowledge workers using the case management system 300as the assigned tasks are being completed. In embodiments, when arequest for a resource used in a task is received and processed by thecase management system 300, the activity monitor component 340 can beconfigured to detect the activity associated with the task. In response,the activity monitor component 340 may be configured to correlate therequested resource with the task and to store the correlation in a tasktable 344. For example, when the requested resource is received from thedata manager 245, a resource identifier associated with the resource canbe generated or detected, and stored in a task table 344 that correlatesthe task with the resource. The activity monitor component 340 may beconfigured to store the resource identifiers associated with therequested resources for at least each task of the plurality of tasksstored in the work queue 230 in the task table 344.

In addition to determining the resources used for each of the firstplurality of tasks, the activity monitor component 340 may also generateanalytic data 342 based on the activities of the knowledge workers asthe assigned tasks are being completed. The activities may include thesearch inquiries of documents, the time spent viewing and analyzing apart of a document, the viewing location in a document, semanticentities in a selected document, filter criteria to generate reports,combination and/or comparisons of the activities, among others.

Once the resources used for each of the plurality of tasks have beendetermined and analytic data 342 have been generated to associate theknowledge worker activities of using the resources to complete theplurality of tasks, a resource list 352 may be generated by the listmanager component 350 for each task cluster 332. In embodiments, theresource list 352 identifies at least one resource used by at least oneknowledge worker to complete the at least two tasks associated with thetask cluster 332. The resource list 352 may comprise resources, such asreports and documents, used by the knowledge worker to complete tasksassociated with the task cluster 332. In addition, the list managercomponent 350 may generate document summaries and store the documentsummaries in the resource list 352. The interaction between the activitymonitor 340 and the list manager 350 to generate the summarized taskview is further illustrated in FIG. 4.

FIG. 4 is a diagram of an exemplary system 400 illustrating theinteraction between the activity monitor 340 and the list manager 350 toprovide a summarized task view. The case management system 400 mayinclude the activity monitor component 340 and the list manager 350. Asshown in FIG. 3, the activity monitor 340 may include the analytic data342 and the task table 344. In addition, the activity monitory 340 mayinclude a filter monitor 412 operatively coupled to a report filterrecorder 414 to record the report-filter criterion-task association inthe task table 344, a search monitor 424 operatively coupled to adocument query monitor 422 and a search semantic analyzer 426 to monitorsearch for documents, a tracking module 432 operatively coupled to ananalytic data collection module 434 to track input device(s) 150 andoutput device(s) 160 and generate the analytic data 342 based on thetracking. Also as shown in FIG. 3, the list manager 350 may include aresource list 352 for each task cluster that includes at least some ofthe resources used by knowledge workers to complete the tasks associatedwith the task cluster. In addition, the list manager 350 may include asemantic entity extraction module 452 operatively coupled to the datastore 105 to extract semantic entities, a search summarizer 454operatively coupled to the search semantic analyzer 426 to generatedocument summaries based on document searches conducted by knowledgeworkers when performing similar tasks, a document view summarizer 456operatively coupled to the analytic data to generate document summaries,and a document summarizer 458.

When a knowledge worker is assigned a task in an underlying case, theknowledge worker may request resource(s), such as documents and reports,from the resource repository 240. In embodiments, the request can be forspecific content in the resource repository 240. Accordingly, therequest can include a filter criterion that identifies the content inthe resource in an embodiment. For example, the knowledge worker can beassigned to complete a task for an insurance claim case that originatedin South Boston. In order to understand the case, the knowledge workermay transmit a request for a resource, e.g., a report detailing crimerate trends over a previous month, including the filter criterion, “CaseOrigin=South Boston.” When the request is received, the task managercomponent 235 may invoke the data manager 245 to retrieve the requestedresource, e.g., the report, from the resource repository 240 and toapply the filter criterion to the retrieved resource. The requestedcontent of the resource may then be transmitted to the requestingknowledge worker. In response to this activity, the activity monitorcomponent 340 may be configured to correlate the requested resource andthe filter criterion with the task and to store the correlation in thetask table 344.

During the report request and response process, the filter monitorcomponent 412 in the activity monitor 340 may monitor each filtercriterion used to generate the report. And over time, the filter monitorcomponent 412 in the activity monitor 340 may monitor each filtercriterion used to generate the reports when performing similar tasks inthe task cluster. Upon detecting the filter criteria and the reportsrequested, the report filter recorder 414 may associate the filtercriterion and the report with the task and store the correlation in thetask table 344.

Once the activity monitor component 340 has recorded the correlation inthe task table 344, the list manager component 350 may be configured togenerate the resource list 352 for a task cluster by determining whichof the plurality of resources were used to complete the tasks in thetask cluster. For example, the list manager component 350 can receivefrom the task categorizer 330 a task cluster that includes a first taskand a second task, and can, for the first task, determine whichresource(s) were used to complete the first task, for example, byreferring to the task table 344 managed by the activity monitorcomponent 340. In a similar manner, the list manager 350 may determinethe resources used to complete the second task in the task cluster. Eachof the determined resources may then identified, e.g., by theirrespective resource identifiers, in the resource list 352 for the taskcluster. In embodiments, when a resource is correlated with additionalinformation, such as a filter criterion applied to the resource recordedby the report filter recorder 414, the resource list 352 for the taskcluster 332 may identify both the resource and the additional correlatedinformation, e.g., the filter criterion. The reports along with thecorrelated additional information, such as the filter criteria stored inresource list 352 may then be presented in a summarized task view in asimilar task.

In embodiments, the request from the knowledge worker can include asearch query for resources that satisfy the query. For example, when theknowledge worker is completing a task for an insurance claim from SouthBoston, the knowledge worker can send a request for resources thatincludes a search query for documents related to South Boston. In thiscase, the case management system may be configured to identify aplurality of resources satisfying the search query, and may return asearch result identifying links to the plurality of resources. When thesearch result is received by the knowledge worker, the knowledge workermay select a resource and send an indication to access the resource tothe case management system. When received, the case management systemcan be configured to retrieve and return the selected resource to theknowledge worker.

In response to this activity, the document query monitor 422 in theactivity monitor component may be configured to monitor a search queryand the documents satisfying the search query, the search monitor 424may detect a request to access a selected document of the documents andcorrelate the selected document with the task and to store thecorrelation in the task table 344. In addition, the search semanticanalyzer 426 can be configured, in an embodiment, to determine why theselected resource is relevant to the task. According to embodiments, thesearch semantic analyzer 426 can be configured to compare semanticentities in the selected resource with the search query and with thecase metadata of the case with which the task is associated to determinewhy the identified resource is relevant to the task. For example, whenthe task is for the insurance claim from South Boston, the selecteddocument may have the name of the claimant or the name of an automobilerepair shop, both of which are likely found in the case metadata. Thisdetermination of relevancy may also be stored in the task table 344along with the selected resource and the task.

In embodiments, the search monitor 424 may also detect a keyword searchconducted inside the selected document. Upon detecting the keywordsearch, the search semantic analyzer 426 may compare semantic entitiesin the selected resource with the keyword and with the case metadata ofthe case with which the task is associated to determine what keywordsthe knowledge worker was looking for inside the document, and why thekeywords are relevant to the task. This determination of relevancy mayalso be stored in the task table 344 along with the keywords, theselected resource, and the task. According to embodiments, once therelevancy is determined based on the comparison result, the searchsummarizer 454 in the list manager 350 can generate resource summariesbased on the semantic entities and the comparison result. The resourcesummaries generated by the search summarizer 454 may then be stored inthe resource list 352 for a task cluster along with the selectedresource. And the resource summaries may be presented in a summarizedtask view of a similar task in the task cluster.

According to embodiments, the activity monitor component 340 candetermine for each of the plurality of tasks, which resources, e.g.,reports and documents, the knowledge workers viewed and read to completethe tasks. For example, when the requested resources, such as documents,are viewed on an output device, the tracking module 432 in the activitymonitor component 340 can be configured to receive an output signal fromthe output device 160 and an input signal from the input device 150indicative of a view location and a view time in the documents. The viewlocation and the view time tracking by the tracking module 432 may beused by the analytic data collection module 434 to generate the analyticdata 342 indicating the viewing pattern of knowledge workers whenperforming similar tasks, such as which part of a document the knowledgeworkers spent most time etc. In addition, the analytic data collectionmodule 434 may be configured to determine why the knowledge workers wereinterested in this information based on similarities between casemetadata and semantic entities extracted from the resources. Havinggenerated the analytic data 342, the document view summarizer 456 in thelist manager 350 may generate resource summaries based on the analyticdata, such as generating a summary of a document based on the analyticdata indicating knowledge workers spent most time viewing a part of thedocument. The resource summaries generated by the document viewsummarizer 456 may be stored in the resource list 352 for a taskcluster. And the resource summaries may then be presented in asummarized task view of a similar task in the task cluster.

In addition to the search summarizer 454 and the document viewsummarizer 456, summaries of resources may also be extracted fromresources by the semantic entity extraction module 452. The semanticentity extraction module 452 may extract semantic entities fromresources stored in the data store 105, such as documents. The extractsemantic entities may then be stored in the resource list 352 andpresented in a summarized task view as summaries of resources in asimilar task.

The resource summaries generated by the semantic entity extractionmodule 452, the search summarizer 454, and the document view summarizer456 may be further processed by the document summarizer 458 to improvethe accuracy of the summaries. In embodiments, the document summarizer458 may apply document summarization algorithms known in the art to theresource summaries stored in the resource list 352. Examples of thedocument summarization algorithm include the event indexing andsummarization (EIS) algorithm (Yi Guo and George Stylios, An IntelligentAlgorithm for Automatic Document Summarization, Heriot-Watt University,which is incorporated by reference herein in its entirety). Otherdocument summarization algorithms may also be used in place of and/or inconjunction with the EIS algorithm. In embodiments, instead of applyingthe document summarization algorithms to the resource summaries storedin the resource list 352, the document summarizer 458 may apply thedocument summarization algorithms directly to the resources stored inthe data store 105 to generate resource summaries. The resourcesummaries generated by the document summarizer 458 may be stored in theresource list 352 for a task cluster. And the resource summariesgenerated by the document summarizer 458 may be presented in asummarized task view of a similar task the task cluster.

FIG. 5 is an exemplary user interface 500 presenting a summarized taskview according to an exemplary embodiment. When a task is assigned to aknowledge worker by the task manager 235, the summarized task view 500may be presented to the knowledge worker as suggested reports andsummaries of documents that can be used to complete the task. The userinterface 500 may include a task identifier 510 identifying the task theknowledge worker is assigned, a case identifier 515 identifying theunderlying case the task is associated with, a task pane 520 to acceptthe knowledge worker input to the task, e.g., yes or no to a loanapproval and notes etc., at least one report 525, and at least onedocument summary 530.

The at least one report 525 along with correlated additionalinformation, such as filter criteria applied to the at least one report525 may be retrieved from the resource list 352. Though FIG. 5 shown tworeports in the exemplary user interface 500, the number of reportsdisplayed may not be limited. Depending on the task configuration, inembodiments, a threshold can be applied to display most commonly usedreports stored in the resource list 352.

In addition to reports, a plurality of document summaries may bedisplayed in the summarized task view 500. Similar to the reportdisplay, the number of document summaries displayed may be limited orunlimited, depending on the task configuration. In a document summary530, summaries may be provided, and links may be attached to thesummaries so that the knowledge worker may follow the link to thecorresponding resources.

For example, as shown in FIG. 5, in a payment history document summary,a list of months representing available monthly payments are displayedas document summaries, and links 540 to the monthly payments documentsmay be attached to the list of months, so that when the knowledge clickson a link, the monthly payment document for the assigned task in thecase may be displayed. And as shown in FIG. 5, in another example, in acustomer employment verification document summary view, a link 550 maybe attached to the summary of a prior employment. Following the link550, the knowledge worker may view the resource, such as an employmentverification document from the prior employment.

The summaries in each document summary view may be generated by thecomponents in the list manager as shown in FIG. 4 based on activitiesperformed by knowledge workers in similar tasks. Accordingly, when aknowledge worker is assigned to perform the task, he or she hasimmediate access to searches and queries used by other knowledge workersin performing similar cases and tasks. And the resource summaries mayhelp the knowledge worker to identify key information for completing thetask. Further, by following the links provides in the resourcesummaries, the knowledge worker may have access to resources used byother knowledge workers to complete similar tasks. The generation of thesummarized task view 500 and the use of the summarized task view 500 ina case management system are further illustrated in FIG. 6.

FIG. 6 is a diagram of an exemplary case management system 600 forgenerating and using a summarized task view to perform a task accordingto an exemplary embodiment. In the case management system 600, when aknowledge worker 610 is assigned to work on a task in a case 620 via thetask manager component 235, the task manager component 235 may invokethe case categorizer 320 and/or the task categorizer 330 to retrieve thecase cluster 324 associated with the task's underlying case 620 and/orthe tasks' task cluster 332 respectively.

The case categorizer 320 may look through the case cluster 324,determine to which cases the underlying case 620 is related, and locaterelated cases in the case cluster 324. The underlying case 620 may sharea case similarity factor with at least another case in the case cluster324. Such cases sharing the case similarity factor may be located by thecase categorizer 320, and in embodiments, the case categorizer 320 cangenerate a case list identifying the cases in the case cluster 324sharing the case similarity factor. According to embodiments, the casesimilarity factor may be related to at least one of geographical casespecific parameters and contextual case specific parameters.

Similar allocation of the task cluster 332 may be performed by the taskcategorizer component 330 to look through the task cluster 332,determine to which tasks in these related cases the assigned task isrelated, and locate related tasks in the task cluster 332 associatedwith the cases in the case cluster 324 sharing the case similarityfactor. The assigned task may share a task similarity factor with atleast another task in the task cluster 332. Such tasks sharing the tasksimilarity factor may be located by the task categorizer 330, and inembodiments, the task categorizer 330 can generate a task listidentifying the tasks in the task cluster 332 sharing the tasksimilarity factor. According to embodiments, the task similarity factormay be is related to the case similarity factor and task specificparameters.

In embodiments, the task manager component 235 may invoke the listmanager component 350 to retrieve the resource list 352 for the taskcluster 332 with which the assigned task is associated and in which theassigned task is included. The list manager component 350 may locate theresource list 352 based on determinations, such as which reports andfilters users have used on performing similar tasks, and/or whichdocuments users have opened on similar tasks. Once the resources used toperform similar tasks in similar cases have been identified, theresources, such as reports and document summaries, may be generated andprovided in a summarized task view 630 to the knowledge worker 610.

An exemplary summarized task view 630 user interface is illustrated inFIG. 5. The summarized task view 630 may be generated by components inthe list manager 350 as shown in FIG. 4. Upon viewing the reports andthe document summaries, the knowledge worker may request resources byfollowing the links provided in the summarized task view 630. Accordingto embodiments, when the requested resource(s) are requested, retrievedand returned, the activity monitor component 340, while continuouslymonitoring the system 600, can be configured to update the task table344 to indicate that the requested resource(s) were used to complete thetask.

In embodiments, when the task table 344 is updated, the list managercomponent 350 can also be invoked to update the resource list 352 forthe task cluster with which the task is associated. For example, whenthe requested resource is in the resource list 352, the list manager 350can be configured, in an embodiment, to update the cluster rating ofeach resource 328 identified in the resource list 352 and to reorder theresources in the resource list 352 based on the updated cluster ratings.According to embodiments, an existing resource in the resource list 352can be removed from the resource list 352 when the resource's updatedcluster rating is below a minimum threshold value. Alternatively, whenthe requested resource 328 b is a new resource not included in theresource list 352, the list manager 350 can be configured, in anotherembodiment, to add information identifying the new resource to theresource list 352. Based on the resource list 352, the summarized taskview 630 may be updated to reflect the updated cluster rating meetingthe minimum threshold value.

In addition or alternatively, the case categorizer component 320, taskcategorizer component 330 and list manager component 350 in the server110 may be configured to categorize case, tasks, and update the resourcelist 352 periodically to ensure that the case clusters 324, the taskclusters 332 and the resource lists 342 are representative of currenttask characteristics and utilized resources respectively. For example,the task categorizer 330 can be configured to collect the most recentinformation related to and/or relevant to a most recent plurality ofcompleted tasks, e.g., the task metadata and case metadata correspondingto each task, and to apply the clustering algorithm to the most recentinformation related to and/or relevant to the most recent plurality ofcompleted tasks to identify new and/or updated tasks clusters 332. Thelist manager component 350 may then generate new and/or updated resourcelists 342 for each new and/or updated task cluster 332. Thus, the caseclusters 324, the task clusters 332 and the resources in the resourcelists 342 may be dynamic; trends in the case metadata and the emergenceof new resources may be detected and captured; and the dynamicinformation may be reflected in the summarized task view 630 to assistthe knowledge worker identifying key information for completing theassigned task.

FIG. 7 is a diagram of a computer implemented method 700, according toembodiments, to provide a summarized task view in a case managementsystem. The computer implemented method 700 may be carried out by, forexample, at least some of the components in the exemplary arrangement ofcomponents illustrated in FIG. 3 and FIG. 4. The arrangement ofcomponents in FIG. 3 and FIG. 4 may be implemented by the components ofthe computing environment 100 of FIG. 1. The case management process maystart by executing an operation 710 by the case categorizer 320 residingon the server 110 to identify among the plurality of cases of the casemanagement system 300, a plurality of case clusters 324. Each casecluster 324 may be associated with a case similarity factor shared by atleast two cases of the case cluster 324. In embodiments, the server 110can be included in the task manager component 235 in the case managementsystem 300, and can have access to the data store 105 via the datamanager 245. In another embodiment, the server 110 can be providedoutside of the case management system 300 as a separate component andconfigured to interact with more than one case management system 300 ina distributed environment.

Upon categorizing the plurality of cases into the plurality of caseclusters 324, an operation 720 may be executed by the task categorizer330 residing on the server 110 to identify, for a case cluster of theplurality of case clusters 324, a plurality of task clusters 332. Eachof the plurality of task cluster 332 may be associated with a tasksimilarity factor shared by at least two tasks of the task cluster, andtasks of the plurality of task clusters are performed on cases of thecase cluster. The task similarity factor may be derived from a semanticanalysis of information related to and/or relevant to each task. Forexample, the related and/or relevant information can include taskmetadata related to a task and/or case metadata associated with anunderlying case for which the task is performed.

Having categorized the cases and the tasks, an operation 730 is executedby the activity monitor 340 residing on the server 110 to analyzeresources, such as reports and documents, used to perform the at leasttwo tasks of the task cluster sharing the task similarity factor. Theactivity monitor 340 may monitor the knowledge worker's activities andresources used by the knowledge worker to complete the tasks. Inaddition, the activity monitor 340 may collect analytic data 342 frommonitoring the activities and the resources. Based on the analytic data342 collected and the analysis by the activity monitor 340, an operation740 is executed by the list manager 350 residing on the server 110 toprovide at least one report based on the reports generated by knowledgeworkers when performing similar tasks and at least one summary based onthe documents used by the knowledge worker when performing similartasks. The similar tasks and the task assigned to the knowledge workershare the task similarity factor in a task cluster. An exemplarysummarized task view user interface is illustrated in FIG. 5.

For the sake of clarity, the processes and methods herein have beenillustrated with a specific flow, but it should be understood that othersequences may be possible and that some may be performed in parallel,without departing from the spirit of the system and method.Additionally, steps may be subdivided or combined.

All references cited herein are intended to be incorporated byreference. Although the present system and method has been describedabove in terms of specific embodiments, it is anticipated thatalterations and modifications to this system and method will no doubtbecome apparent to those skilled in the art and may be practiced withinthe scope and equivalents of the appended claims. More than one computermay be used, such as by using multiple computers in a parallel orload-sharing arrangement or distributing tasks across multiple computerssuch that, as a whole, they perform the functions of the componentsidentified herein; i.e. they take the place of a single computer.Various functions described above may be performed by a single processor groups of processes, on a single computer or distributed over severalcomputers. Processes may invoke other processes to handle certain tasks.A single storage device may be used, or several may be used to take theplace of a single storage device. The present embodiments are to beconsidered as illustrative and not restrictive, and the system andmethod is not to be limited to the details given herein. It is thereforeintended that the disclosure and following claims be interpreted ascovering all such alterations and modifications as fall within the truespirit and scope of the system and method.

What is claimed is:
 1. A computer implemented method for providinginformation related to a task in a case management system configured toprocess a plurality of cases, the computer implemented methodcomprising: monitoring, by a server, requests for resources used toperform a plurality of tasks and storing correlations between therequested resources and tasks from the plurality of tasks; clusteringthe plurality of cases, by the server, into a plurality of caseclusters, wherein each of the plurality of case clusters is associatedwith a case similarity factor shared by at least two cases of theplurality of cases; for a case cluster of the plurality of caseclusters, identifying, by the server, a plurality of task clusters,wherein each of the plurality of task clusters is associated with a tasksimilarity factor shared by at least two tasks of the task cluster, andtasks of the plurality of task clusters are performed on cases of thecase cluster; analyzing, by the server, reports and documents used toperform the at least two tasks of the task cluster sharing the tasksimilarity factor; associating, by the server, the reports and documentsused to perform the at least two tasks of the task cluster sharing thetask similarity factor with the task cluster associated with the tasksimilarity factor; and when performing a task sharing the tasksimilarity factor with the at least two tasks of the task clustersharing the task similarity factor, providing, by the server, to aremote computer, at least one report based on the reports associatedwith the task cluster and at least one summary based on the documentsassociated with the task cluster.
 2. The method of claim 1, furthercomprising: prior to performing a new task on an underlying case,determining, by the server, with which case cluster the underlying caseis associated and identifying with which task cluster of the determinedcase cluster the new task is associated; including, by the server, thenew task in the identified task cluster; and providing, by the server,the at least one report and the at least one summary to facilitateperforming the new task.
 3. The method of claim 1, wherein analyzing, bythe server, the reports and the documents used to perform the at leasttwo tasks of the task cluster sharing the task similarity factorincludes: monitoring, by the server, a filter criterion to generate thereports; and associating, by the server, the fitter criterion and thereports with the at least two tasks.
 4. The method of claim 1, whereinanalyzing, by the server, the reports and the documents used to performthe at least two tasks of the task cluster sharing the task similarityfactor includes: monitoring, by the server, when the documentssatisfying a search query included in a request for the documents isidentified; detecting, by the server, a request to access a selecteddocument of the documents; and comparing semantic entities in theselected document with the search query and with case metadata of thecase with which the task is associated to determine why the selecteddocument is relevant to the task.
 5. The method of claim 4, wherein theat least one summary is generated based on the semantic entities and aresult of the comparing the semantic entities in the selected documentwith the search query and with case metadata.
 6. The method of claim 1,wherein the at least one summary is generated based on searchesconducted inside the documents when performing the task, and thesearches include keyword searches of the documents.
 7. The method ofclaim 1, wherein the at least one summary is generated based on analyticdata collected when the documents are viewed to perform the task, andthe analytic data collection includes input device tracking and outputdevice tracking when the documents are viewed.
 8. The method of claim 1,wherein the at least one summary is generated by applying a documentsummarization algorithm to searches conducted inside the documents, atracking of document review, and semantic entities extracted from thedocuments.
 9. The method of claim 1, wherein the case similarity factoris related to at least one of geographical case specific parameters andcontextual case specific parameters.
 10. The method of claim 9, whereinidentifying among the plurality of cases, by the server, the pluralityof case clusters includes: extracting semantic entities from theplurality of cases; creating at least one data vector based at least oncase metadata and the semantic entities of each of the plurality ofcases; and using the at least one data vector to categorize theplurality of cases into the plurality of case clusters based on the casesimilarity factor.
 11. The method of claim 9, wherein for the casecluster of the plurality of case clusters, identifying, by the server,the plurality of task clusters includes: based on the task similarityfactor, using task metadata, case metadata, and semantic entities tocategorize the tasks into the plurality of task clusters, wherein thesemantic entities are extracted from case documents used in performingthe tasks, wherein the task similarity factor is related to the casesimilarity factor and task specific parameters.
 12. A system forproviding information related to a task in a case management systemconfigured to process a plurality of cases, the system comprising: acase categorizer, residing on a server, to identify among the pluralityof cases a plurality of case clusters, wherein each of the plurality ofcase clusters is associated with a case similarity factor shared by atleast two cases of the plurality of cases; a task categorizer,operatively coupled to the case categorizer, for a case cluster of theplurality of case clusters, to identifying a plurality of task clusters,wherein each of the plurality of task cluster is associated with a tasksimilarity factor shared by at least two tasks of the task cluster, andtasks of the plurality of task clusters are performed on cases of thecase cluster; an activity monitor, operatively coupled to the casecategorizer and the task categorizer, to monitor requests for resourcesused to perform a plurality of tasks and store correlations between therequested resources and tasks from the plurality of tasks, and toanalyze reports and documents used to perform the at least two tasks ofthe task cluster sharing the task similarity factor and collect analyticdata based on an analysis of the reports and documents; and a listmanager, operatively coupled to the activity monitor, to associate thereports and documents used to perform the at least two tasks of the taskcluster sharing the task similarity factor with the task clusterassociated with the task similarity factor, and when the server executesa task sharing the task similarity factor with the at least two tasks ofthe task cluster sharing the task similarity factor, to provide to aremote computer at least one report based on the reports associated withthe task cluster and at least one summary based on the documentsassociated with the task cluster.
 13. The system of claim 12, whereinthe activity monitor includes: a filter monitor to monitor a filtercriterion to generate a report in the reports when performing a task inthe task cluster; and a report filter recorder to associate the filtercriterion and the report with the task.
 14. The system of claim 12,wherein the activity monitor includes: a document query monitor tomonitor a search query and the documents satisfying the search query; asearch monitor to detect a request to access a selected document of thedocuments and detect keywords searched inside the selected documents;and a search semantic analyzer to compare semantic entities in theselected document with the search query, the keyword, and with casemetadata of the case with which the task is associated to determine whythe selected document and the keywords are relevant to the task.
 15. Thesystem of claim 14, wherein the list manager includes: a searchsummarizer to generate the at least one summary based on the semanticentities and a result of a comparison among semantic entities in theselected document with the search query, the keyword and the casemetadata of the case.
 16. The system of claim 12, wherein the activitymonitor includes: a tracking module, when the documents are viewed on anoutput device, to receive an output signal from the output device and aninput signal from an input device indicative of a view location and aview time in the documents; and an analytic data collection module togenerate analytic data based on the view location and the view time inthe documents, wherein the analytic data indicates which parts of thedocuments are viewed the most.
 17. The system of claim 16, wherein thelist manager includes: a document view summarizer to generate the atleast one summary based on the analytic data when executing the task.18. The system of claim 12, wherein the list manager includes: asemantic entity extraction module to generate the at least one summarybased on semantic entities extracted from the documents.
 19. The systemof claim 12, wherein the list manager includes: a document summarizer togenerate the at least one summary by applying a document summarizationalgorithm to searches conducted inside the documents, a documenttracking, and semantic entities extracted from the documents.
 20. Amachine-readable medium including instructions embodied in a tangible,non-transitory, computer readable storage medium and comprising computerinstructions executable by a processor to perform a computer implementedmethod for providing information related to a task in a case managementsystem configured to process a plurality of cases, the computerimplemented method comprising: monitoring, by a server, requests forresources used to perform a plurality of tasks and storing correlationsbetween the requested resources and tasks from the plurality of tasks;clustering, by the server, a plurality of cases into a plurality of caseclusters, wherein each of the plurality of case clusters is associatedwith a case similarity factor shared by at least two cases of theplurality of cases; for a case cluster of the plurality of caseclusters, identifying, by the server, a plurality of task clusters,wherein each of the plurality of task clusters is associated with a tasksimilarity factor shared by at least two tasks of the task cluster, andtasks of the plurality of task clusters are performed on cases of thecase cluster; analyzing, by the server, reports and documents used toperform the at least two tasks of the task cluster sharing the tasksimilarity factor; associating, by the server, the reports and documentsused to perform the at least two tasks of the task cluster sharing thetask similarity factor with the task cluster associated with the tasksimilarity factor; and when performing a task sharing the tasksimilarity factor with the at least two tasks of the task clustersharing the task similarity factor, providing, by the server, to aremote computer, at least one report based on the reports associatedwith the task cluster and at least one summary based on the documentsassociated with the task cluster.